{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "import QUANTAXIS as QA\n",
    "import numpy as np;\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "stock_list = QA.QA_fetch_get_stock_list('tdx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              code  volunit  decimal_point   name     pre_close sse       sec\n",
      "code   sse                                                                   \n",
      "000001 sz   000001      100              2   平安银行  1.416040e+03  sz  stock_cn\n",
      "000002 sz   000002      100              2   万 科Ａ  2.736000e+01  sz  stock_cn\n",
      "000004 sz   000004      100              2   国农科技  1.816000e+01  sz  stock_cn\n",
      "000005 sz   000005      100              2   世纪星源  2.946011e+03  sz  stock_cn\n",
      "000006 sz   000006      100              2   深振业Ａ  4.950000e+00  sz  stock_cn\n",
      "000007 sz   000007      100              2    全新好  7.100000e+00  sz  stock_cn\n",
      "000008 sz   000008      100              2   神州高铁  6.338013e+03  sz  stock_cn\n",
      "000009 sz   000009      100              2   中国宝安  4.260000e+00  sz  stock_cn\n",
      "000010 sz   000010      100              2  *ST美丽  6.018011e+03  sz  stock_cn\n",
      "000011 sz   000011      100              2   深物业A  2.160175e+02  sz  stock_cn\n",
      "000012 sz   000012      100              2   南 玻Ａ  7.746009e+03  sz  stock_cn\n",
      "000014 sz   000014      100              2   沙河股份  1.360300e+02  sz  stock_cn\n",
      "000016 sz   000016      100              2   深康佳Ａ  7.362003e+03  sz  stock_cn\n",
      "000017 sz   000017      100              2   深中华A  7.746009e+03  sz  stock_cn\n",
      "000018 sz   000018      100              2  *ST神城  1.160000e+00  sz  stock_cn\n",
      "000019 sz   000019      100              2   深粮控股  5.980000e+00  sz  stock_cn\n",
      "000020 sz   000020      100              2   深华发Ａ  4.560100e+02  sz  stock_cn\n",
      "000021 sz   000021      100              2    深科技  7.550000e+00  sz  stock_cn\n",
      "000023 sz   000023      100              2   深天地Ａ  1.016052e+03  sz  stock_cn\n",
      "000025 sz   000025      100              2   特 力Ａ  1.793000e+01  sz  stock_cn\n",
      "000026 sz   000026      100              2   飞亚达Ａ  6.990000e+00  sz  stock_cn\n",
      "000027 sz   000027      100              2   深圳能源  5.530000e+00  sz  stock_cn\n",
      "000028 sz   000028      100              2   国药一致  1.560100e+02  sz  stock_cn\n",
      "000029 sz   000029      100              2   深深房Ａ  7.600325e+02  sz  stock_cn\n",
      "000030 sz   000030      100              2   富奥股份  4.510000e+00  sz  stock_cn\n",
      "000031 sz   000031      100              2    大悦城  6.600000e+00  sz  stock_cn\n",
      "000032 sz   000032      100              2   深桑达Ａ  2.480125e+02  sz  stock_cn\n",
      "000034 sz   000034      100              2   神州数码  1.272042e+03  sz  stock_cn\n",
      "000035 sz   000035      100              2   中国天楹  4.860000e+00  sz  stock_cn\n",
      "000036 sz   000036      100              2   华联控股  4.330000e+00  sz  stock_cn\n",
      "...            ...      ...            ...    ...           ...  ..       ...\n",
      "603998 sh   603998      100              2   方盛制药  6.020000e+00  sh  stock_cn\n",
      "603999 sh   603999      100              2   读者传媒  4.730000e+00  sh  stock_cn\n",
      "688001 sh   688001      100              2   华兴源创  7.660000e+01  sh  stock_cn\n",
      "688002 sh   688002      100              2   睿创微纳  6.550000e+01  sh  stock_cn\n",
      "688003 sh   688003      100              2   天准科技  5.120100e+02  sh  stock_cn\n",
      "688005 sh   688005      100              2   容百科技  5.042000e+02  sh  stock_cn\n",
      "688006 sh   688006      100              2   杭可科技  7.369000e+01  sh  stock_cn\n",
      "688007 sh   688007      100              2   光峰科技  3.842000e+02  sh  stock_cn\n",
      "688008 sh   688008      100              2   澜起科技  7.913000e+01  sh  stock_cn\n",
      "688009 sh   688009      100              2   中国通号  9.840175e+02  sh  stock_cn\n",
      "688010 sh   688010      100              2   福光股份  7.718000e+01  sh  stock_cn\n",
      "688011 sh   688011      100              2   新光光电  8.752000e+01  sh  stock_cn\n",
      "688012 sh   688012      100              2   中微公司  9.001000e+01  sh  stock_cn\n",
      "688015 sh   688015      100              2   交控科技  4.762100e+02  sh  stock_cn\n",
      "688016 sh   688016      100              2   心脉医疗  1.675000e+02  sh  stock_cn\n",
      "688018 sh   688018      100              2   乐鑫科技  1.656600e+02  sh  stock_cn\n",
      "688019 sh   688019      100              2   安集科技  1.830000e+02  sh  stock_cn\n",
      "688020 sh   688020      100              2   方邦股份  1.230000e+02  sh  stock_cn\n",
      "688022 sh   688022      100              2   瀚川智能  8.250000e+01  sh  stock_cn\n",
      "688028 sh   688028      100              2    沃尔德  1.292600e+02  sh  stock_cn\n",
      "688029 sh   688029      100              2   南微医学  1.270700e+02  sh  stock_cn\n",
      "688033 sh   688033      100              2   天宜上佳  4.121700e+02  sh  stock_cn\n",
      "688066 sh   688066      100              2   航天宏图  5.442000e+02  sh  stock_cn\n",
      "688088 sh   688088      100              2   虹软科技  7.499000e+01  sh  stock_cn\n",
      "688099 sh   688099      100              2    N晶晨  1.360000e+02  sh  stock_cn\n",
      "688122 sh   688122      100              2   西部超导  5.081700e+02  sh  stock_cn\n",
      "688188 sh   688188      100              2    N柏楚  6.858000e+01  sh  stock_cn\n",
      "688321 sh   688321      100              2   微芯生物  5.877472e-39  sh  stock_cn\n",
      "688333 sh   688333      100              2    铂力特  1.005500e+02  sh  stock_cn\n",
      "688388 sh   688388      100              2   嘉元科技  7.250000e+01  sh  stock_cn\n",
      "\n",
      "[3677 rows x 7 columns]\n"
     ]
    }
   ],
   "source": [
    "print(stock_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(stock_list.code)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_star_block = stock_list.code[(stock_list.code) > '688000']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['688001' '688002' '688003' '688005' '688006' '688007' '688008' '688009'\n",
      " '688010' '688011' '688012' '688015' '688016' '688018' '688019' '688020'\n",
      " '688022' '688028' '688029' '688033' '688066' '688088' '688099' '688122'\n",
      " '688188' '688321' '688333' '688388']\n",
      "<class 'QUANTAXIS.QAData.QADataStruct.QA_DataStruct_Stock_day'>\n"
     ]
    }
   ],
   "source": [
    "aa= np.asarray(new_star_block)\n",
    "print(aa)\n",
    "aa_list = aa.tolist()\n",
    "data_open=QA.QA_fetch_stock_day_adv(aa_list,'2019-07-22','2019-07-22')\n",
    "\n",
    "print(type(data_open))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.series.Series'>\n",
      "open      5.540000e+01\n",
      "high      7.202000e+01\n",
      "low       3.959000e+01\n",
      "close     5.550000e+01\n",
      "volume    2.901070e+05\n",
      "amount    1.507398e+09\n",
      "Name: (2019-07-22 00:00:00, 688001), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      5.910000e+01\n",
      "high      6.028000e+01\n",
      "low       3.000000e+01\n",
      "close     5.020000e+01\n",
      "volume    4.150030e+05\n",
      "amount    1.895111e+09\n",
      "Name: (2019-07-22 00:00:00, 688002), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      5.580000e+01\n",
      "high      7.060000e+01\n",
      "low       3.089000e+01\n",
      "close     4.740000e+01\n",
      "volume    3.270430e+05\n",
      "amount    1.495912e+09\n",
      "Name: (2019-07-22 00:00:00, 688003), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      4.258000e+01\n",
      "high      6.813000e+01\n",
      "low       3.512000e+01\n",
      "close     4.953000e+01\n",
      "volume    3.236000e+05\n",
      "amount    1.445110e+09\n",
      "Name: (2019-07-22 00:00:00, 688005), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      4.900000e+01\n",
      "high      7.499000e+01\n",
      "low       3.768000e+01\n",
      "close     5.462000e+01\n",
      "volume    2.923710e+05\n",
      "amount    1.457131e+09\n",
      "Name: (2019-07-22 00:00:00, 688006), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      3.502000e+01\n",
      "high      5.200000e+01\n",
      "low       2.645000e+01\n",
      "close     3.884000e+01\n",
      "volume    4.510280e+05\n",
      "amount    1.547721e+09\n",
      "Name: (2019-07-22 00:00:00, 688007), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      9.130000e+01\n",
      "high      9.720000e+01\n",
      "low       6.630000e+01\n",
      "close     7.492000e+01\n",
      "volume    5.833060e+05\n",
      "amount    4.564779e+09\n",
      "Name: (2019-07-22 00:00:00, 688008), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.170000e+01\n",
      "high      1.521000e+01\n",
      "low       7.690000e+00\n",
      "close     1.227000e+01\n",
      "volume    9.236244e+06\n",
      "amount    9.762394e+09\n",
      "Name: (2019-07-22 00:00:00, 688009), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      4.003000e+01\n",
      "high      6.405000e+01\n",
      "low       3.612000e+01\n",
      "close     4.867000e+01\n",
      "volume    2.637180e+05\n",
      "amount    1.198530e+09\n",
      "Name: (2019-07-22 00:00:00, 688010), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      6.000000e+01\n",
      "high      9.600000e+01\n",
      "low       5.001000e+01\n",
      "close     7.017000e+01\n",
      "volume    1.740250e+05\n",
      "amount    1.125677e+09\n",
      "Name: (2019-07-22 00:00:00, 688011), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.098000e+02\n",
      "high      1.250000e+02\n",
      "low       6.200000e+01\n",
      "close     8.103000e+01\n",
      "volume    3.652010e+05\n",
      "amount    3.090029e+09\n",
      "Name: (2019-07-22 00:00:00, 688012), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      4.080000e+01\n",
      "high      4.956000e+01\n",
      "low       2.400000e+01\n",
      "close     3.790000e+01\n",
      "volume    2.485960e+05\n",
      "amount    8.403589e+08\n",
      "Name: (2019-07-22 00:00:00, 688015), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.420000e+02\n",
      "high      2.190300e+02\n",
      "low       1.010000e+02\n",
      "close     1.583000e+02\n",
      "volume    1.181540e+05\n",
      "amount    1.663379e+09\n",
      "Name: (2019-07-22 00:00:00, 688016), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.524500e+02\n",
      "high      1.688800e+02\n",
      "low       9.900000e+01\n",
      "close     1.291100e+02\n",
      "volume    1.336480e+05\n",
      "amount    1.723144e+09\n",
      "Name: (2019-07-22 00:00:00, 688018), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.520000e+02\n",
      "high      2.432000e+02\n",
      "low       1.100000e+02\n",
      "close     1.960100e+02\n",
      "volume    9.976800e+04\n",
      "amount    1.582281e+09\n",
      "Name: (2019-07-22 00:00:00, 688019), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.060000e+02\n",
      "high      1.364900e+02\n",
      "low       7.474000e+01\n",
      "close     1.011000e+02\n",
      "volume    1.406300e+05\n",
      "amount    1.321166e+09\n",
      "Name: (2019-07-22 00:00:00, 688020), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      6.760000e+01\n",
      "high      6.899000e+01\n",
      "low       3.353000e+01\n",
      "close     5.019000e+01\n",
      "volume    1.768100e+05\n",
      "amount    8.535892e+08\n",
      "Name: (2019-07-22 00:00:00, 688022), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      5.389000e+01\n",
      "high      7.007000e+01\n",
      "low       3.842000e+01\n",
      "close     5.600000e+01\n",
      "volume    1.370310e+05\n",
      "amount    6.877370e+08\n",
      "Name: (2019-07-22 00:00:00, 688028), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.130200e+02\n",
      "high      1.363700e+02\n",
      "low       8.710000e+01\n",
      "close     1.105100e+02\n",
      "volume    2.009140e+05\n",
      "amount    2.146542e+09\n",
      "Name: (2019-07-22 00:00:00, 688029), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      3.500000e+01\n",
      "high      5.600000e+01\n",
      "low       2.830000e+01\n",
      "close     4.008000e+01\n",
      "volume    3.375120e+05\n",
      "amount    1.213649e+09\n",
      "Name: (2019-07-22 00:00:00, 688033), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      4.300000e+01\n",
      "high      6.850000e+01\n",
      "low       3.060000e+01\n",
      "close     4.760000e+01\n",
      "volume    2.881220e+05\n",
      "amount    1.201783e+09\n",
      "Name: (2019-07-22 00:00:00, 688066), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      8.650000e+01\n",
      "high      8.650000e+01\n",
      "low       4.500000e+01\n",
      "close     6.555000e+01\n",
      "volume    3.024200e+05\n",
      "amount    1.860613e+09\n",
      "Name: (2019-07-22 00:00:00, 688088), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      4.100000e+01\n",
      "high      6.560000e+01\n",
      "low       2.888000e+01\n",
      "close     5.499000e+01\n",
      "volume    3.311010e+05\n",
      "amount    1.358249e+09\n",
      "Name: (2019-07-22 00:00:00, 688122), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      6.100000e+01\n",
      "high      9.600000e+01\n",
      "low       4.340000e+01\n",
      "close     6.433000e+01\n",
      "volume    1.482630e+05\n",
      "amount    8.572497e+08\n",
      "Name: (2019-07-22 00:00:00, 688333), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      6.600000e+01\n",
      "high      7.500000e+01\n",
      "low       3.517000e+01\n",
      "close     5.666000e+01\n",
      "volume    4.015720e+05\n",
      "amount    2.108323e+09\n",
      "Name: (2019-07-22 00:00:00, 688388), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      4.692000e+01\n",
      "high      5.265000e+01\n",
      "low       4.501000e+01\n",
      "close     4.873000e+01\n",
      "volume    1.006060e+05\n",
      "amount    4.959887e+08\n",
      "Name: (2019-07-23 00:00:00, 688001), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      4.016000e+01\n",
      "high      4.750000e+01\n",
      "low       4.001000e+01\n",
      "close     4.389000e+01\n",
      "volume    1.624640e+05\n",
      "amount    7.211881e+08\n",
      "Name: (2019-07-23 00:00:00, 688002), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      3.850000e+01\n",
      "high      4.385000e+01\n",
      "low       3.751000e+01\n",
      "close     4.050000e+01\n",
      "volume    1.265680e+05\n",
      "amount    5.205662e+08\n",
      "Name: (2019-07-23 00:00:00, 688003), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      4.075000e+01\n",
      "high      4.485000e+01\n",
      "low       3.949000e+01\n",
      "close     4.170000e+01\n",
      "volume    1.295300e+05\n",
      "amount    5.514255e+08\n",
      "Name: (2019-07-23 00:00:00, 688005), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      4.500000e+01\n",
      "high      5.050000e+01\n",
      "low       4.312000e+01\n",
      "close     4.711000e+01\n",
      "volume    1.130520e+05\n",
      "amount    5.384975e+08\n",
      "Name: (2019-07-23 00:00:00, 688006), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      3.280000e+01\n",
      "high      3.661000e+01\n",
      "low       3.188000e+01\n",
      "close     3.455000e+01\n",
      "volume    1.873300e+05\n",
      "amount    6.525343e+08\n",
      "Name: (2019-07-23 00:00:00, 688007), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      7.002000e+01\n",
      "high      7.888000e+01\n",
      "low       7.000000e+01\n",
      "close     7.413000e+01\n",
      "volume    2.390600e+05\n",
      "amount    1.777324e+09\n",
      "Name: (2019-07-23 00:00:00, 688008), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      9.880000e+00\n",
      "high      1.098000e+01\n",
      "low       9.610000e+00\n",
      "close     1.001000e+01\n",
      "volume    4.111585e+06\n",
      "amount    4.234133e+09\n",
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      "amount    1.138875e+09\n",
      "Name: (2019-08-07 00:00:00, 688012), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      6.100000e+01\n",
      "high      6.190000e+01\n",
      "low       5.501000e+01\n",
      "close     5.996000e+01\n",
      "volume    1.183700e+05\n",
      "amount    6.935226e+08\n",
      "Name: (2019-08-07 00:00:00, 688015), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open            175.0\n",
      "high            176.5\n",
      "low             160.0\n",
      "close           167.5\n",
      "volume        36748.0\n",
      "amount    615929216.0\n",
      "Name: (2019-08-07 00:00:00, 688016), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.626300e+02\n",
      "high      1.700000e+02\n",
      "low       1.530000e+02\n",
      "close     1.656600e+02\n",
      "volume    6.511200e+04\n",
      "amount    1.058310e+09\n",
      "Name: (2019-08-07 00:00:00, 688018), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.881300e+02\n",
      "high      1.915000e+02\n",
      "low       1.753300e+02\n",
      "close     1.830000e+02\n",
      "volume    3.216600e+04\n",
      "amount    5.880825e+08\n",
      "Name: (2019-08-07 00:00:00, 688019), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.243600e+02\n",
      "high      1.256000e+02\n",
      "low       1.150100e+02\n",
      "close     1.230000e+02\n",
      "volume    5.786300e+04\n",
      "amount    6.962758e+08\n",
      "Name: (2019-08-07 00:00:00, 688020), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      8.199000e+01\n",
      "high      8.556000e+01\n",
      "low       7.891000e+01\n",
      "close     8.250000e+01\n",
      "volume    9.637900e+04\n",
      "amount    7.906872e+08\n",
      "Name: (2019-08-07 00:00:00, 688022), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.280000e+02\n",
      "high      1.370000e+02\n",
      "low       1.245000e+02\n",
      "close     1.292600e+02\n",
      "volume    8.668200e+04\n",
      "amount    1.134465e+09\n",
      "Name: (2019-08-07 00:00:00, 688028), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.310000e+02\n",
      "high      1.320000e+02\n",
      "low       1.236000e+02\n",
      "close     1.270700e+02\n",
      "volume    6.839900e+04\n",
      "amount    8.716532e+08\n",
      "Name: (2019-08-07 00:00:00, 688029), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      5.500000e+01\n",
      "high      5.600000e+01\n",
      "low       5.159000e+01\n",
      "close     5.592000e+01\n",
      "volume    1.372900e+05\n",
      "amount    7.415862e+08\n",
      "Name: (2019-08-07 00:00:00, 688033), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      6.599000e+01\n",
      "high      6.672000e+01\n",
      "low       6.060000e+01\n",
      "close     6.420000e+01\n",
      "volume    1.184630e+05\n",
      "amount    7.545336e+08\n",
      "Name: (2019-08-07 00:00:00, 688066), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      7.857000e+01\n",
      "high      7.860000e+01\n",
      "low       7.100000e+01\n",
      "close     7.499000e+01\n",
      "volume    1.178410e+05\n",
      "amount    8.784260e+08\n",
      "Name: (2019-08-07 00:00:00, 688088), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      6.105000e+01\n",
      "high      6.229000e+01\n",
      "low       5.693000e+01\n",
      "close     6.192000e+01\n",
      "volume    1.289870e+05\n",
      "amount    7.737502e+08\n",
      "Name: (2019-08-07 00:00:00, 688122), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.079000e+02\n",
      "high      1.090000e+02\n",
      "low       9.320000e+01\n",
      "close     1.005500e+02\n",
      "volume    7.816400e+04\n",
      "amount    7.889820e+08\n",
      "Name: (2019-08-07 00:00:00, 688333), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      7.126000e+01\n",
      "high      7.436000e+01\n",
      "low       6.900000e+01\n",
      "close     7.250000e+01\n",
      "volume    1.516250e+05\n",
      "amount    1.088741e+09\n",
      "Name: (2019-08-07 00:00:00, 688388), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      7.400000e+01\n",
      "high      7.560000e+01\n",
      "low       6.880000e+01\n",
      "close     6.903000e+01\n",
      "volume    1.461060e+05\n",
      "amount    1.046579e+09\n",
      "Name: (2019-08-08 00:00:00, 688001), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      6.600000e+01\n",
      "high      7.050000e+01\n",
      "low       6.318000e+01\n",
      "close     6.350000e+01\n",
      "volume    1.820510e+05\n",
      "amount    1.227321e+09\n",
      "Name: (2019-08-08 00:00:00, 688002), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      6.150000e+01\n",
      "high      6.230000e+01\n",
      "low       5.692000e+01\n",
      "close     5.700000e+01\n",
      "volume    9.941900e+04\n",
      "amount    5.899656e+08\n",
      "Name: (2019-08-08 00:00:00, 688003), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      6.120000e+01\n",
      "high      6.201000e+01\n",
      "low       5.601000e+01\n",
      "close     5.610000e+01\n",
      "volume    1.086380e+05\n",
      "amount    6.372922e+08\n",
      "Name: (2019-08-08 00:00:00, 688005), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      7.161000e+01\n",
      "high      7.378000e+01\n",
      "low       6.601000e+01\n",
      "close     6.640000e+01\n",
      "volume    1.204470e+05\n",
      "amount    8.348177e+08\n",
      "Name: (2019-08-08 00:00:00, 688006), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      5.411000e+01\n",
      "high      5.570000e+01\n",
      "low       4.968000e+01\n",
      "close     5.010000e+01\n",
      "volume    1.743330e+05\n",
      "amount    9.106194e+08\n",
      "Name: (2019-08-08 00:00:00, 688007), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      7.930000e+01\n",
      "high      8.389000e+01\n",
      "low       7.803000e+01\n",
      "close     7.849000e+01\n",
      "volume    1.539010e+05\n",
      "amount    1.240953e+09\n",
      "Name: (2019-08-08 00:00:00, 688008), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.173000e+01\n",
      "high      1.187000e+01\n",
      "low       1.118000e+01\n",
      "close     1.122000e+01\n",
      "volume    2.228794e+06\n",
      "amount    2.551001e+09\n",
      "Name: (2019-08-08 00:00:00, 688009), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      7.727000e+01\n",
      "high      7.765000e+01\n",
      "low       7.100000e+01\n",
      "close     7.160000e+01\n",
      "volume    8.411700e+04\n",
      "amount    6.248262e+08\n",
      "Name: (2019-08-08 00:00:00, 688010), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      8.630000e+01\n",
      "high      8.992000e+01\n",
      "low       8.100000e+01\n",
      "close     8.155000e+01\n",
      "volume    6.081200e+04\n",
      "amount    5.151396e+08\n",
      "Name: (2019-08-08 00:00:00, 688011), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      9.000000e+01\n",
      "high      9.255000e+01\n",
      "low       8.650000e+01\n",
      "close     8.650000e+01\n",
      "volume    9.782200e+04\n",
      "amount    8.745994e+08\n",
      "Name: (2019-08-08 00:00:00, 688012), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      5.818000e+01\n",
      "high      5.977000e+01\n",
      "low       5.300000e+01\n",
      "close     5.366000e+01\n",
      "volume    9.789300e+04\n",
      "amount    5.528909e+08\n",
      "Name: (2019-08-08 00:00:00, 688015), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open            168.0\n",
      "high            173.6\n",
      "low             163.8\n",
      "close           163.9\n",
      "volume        30496.0\n",
      "amount    515052608.0\n",
      "Name: (2019-08-08 00:00:00, 688016), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open            165.0\n",
      "high            167.5\n",
      "low             156.2\n",
      "close           156.9\n",
      "volume        44893.0\n",
      "amount    725032832.0\n",
      "Name: (2019-08-08 00:00:00, 688018), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.820000e+02\n",
      "high      1.838800e+02\n",
      "low       1.753500e+02\n",
      "close     1.756600e+02\n",
      "volume    2.167400e+04\n",
      "amount    3.886695e+08\n",
      "Name: (2019-08-08 00:00:00, 688019), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.224600e+02\n",
      "high      1.230600e+02\n",
      "low       1.140500e+02\n",
      "close     1.142100e+02\n",
      "volume    4.301400e+04\n",
      "amount    5.094601e+08\n",
      "Name: (2019-08-08 00:00:00, 688020), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      8.001000e+01\n",
      "high      8.250000e+01\n",
      "low       7.500000e+01\n",
      "close     7.675000e+01\n",
      "volume    7.899600e+04\n",
      "amount    6.181921e+08\n",
      "Name: (2019-08-08 00:00:00, 688022), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.230000e+02\n",
      "high      1.329300e+02\n",
      "low       1.187700e+02\n",
      "close     1.309900e+02\n",
      "volume    8.199400e+04\n",
      "amount    1.031408e+09\n",
      "Name: (2019-08-08 00:00:00, 688028), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.260000e+02\n",
      "high      1.362000e+02\n",
      "low       1.250300e+02\n",
      "close     1.290800e+02\n",
      "volume    7.718300e+04\n",
      "amount    1.013705e+09\n",
      "Name: (2019-08-08 00:00:00, 688029), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open             56.2\n",
      "high             57.8\n",
      "low              52.5\n",
      "close            52.8\n",
      "volume       126826.0\n",
      "amount    703863104.0\n",
      "Name: (2019-08-08 00:00:00, 688033), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open             63.0\n",
      "high             65.8\n",
      "low              58.0\n",
      "close            58.0\n",
      "volume       111318.0\n",
      "amount    679798208.0\n",
      "Name: (2019-08-08 00:00:00, 688066), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      7.499000e+01\n",
      "high      7.659000e+01\n",
      "low       6.969000e+01\n",
      "close     7.000000e+01\n",
      "volume    9.327300e+04\n",
      "amount    6.774497e+08\n",
      "Name: (2019-08-08 00:00:00, 688088), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      1.360000e+02\n",
      "high      1.660000e+02\n",
      "low       1.350000e+02\n",
      "close     1.433600e+02\n",
      "volume    2.804140e+05\n",
      "amount    4.048996e+09\n",
      "Name: (2019-08-08 00:00:00, 688099), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      6.100000e+01\n",
      "high      6.259000e+01\n",
      "low       5.658000e+01\n",
      "close     5.692000e+01\n",
      "volume    9.904700e+04\n",
      "amount    5.875868e+08\n",
      "Name: (2019-08-08 00:00:00, 688122), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      2.170000e+02\n",
      "high      2.780000e+02\n",
      "low       2.156500e+02\n",
      "close     2.438800e+02\n",
      "volume    1.660210e+05\n",
      "amount    4.071389e+09\n",
      "Name: (2019-08-08 00:00:00, 688188), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      9.700000e+01\n",
      "high      9.888000e+01\n",
      "low       9.010000e+01\n",
      "close     9.020000e+01\n",
      "volume    6.603500e+04\n",
      "amount    6.193240e+08\n",
      "Name: (2019-08-08 00:00:00, 688333), dtype: float64\n",
      "<class 'pandas.core.series.Series'>\n",
      "open      7.249000e+01\n",
      "high      7.360000e+01\n",
      "low       6.755000e+01\n",
      "close     6.799000e+01\n",
      "volume    1.257700e+05\n",
      "amount    8.806398e+08\n",
      "Name: (2019-08-08 00:00:00, 688388), dtype: float64\n"
     ]
    }
   ],
   "source": [
    "for i in data:\n",
    "    print(type(i))\n",
    "    print(i)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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